The disclosed method concerns making predictions in respect of media coverage, product sales or stock price performance, following material business developments, positive or negative, such as the win/loss of a major contract, a corporate crisis, an accidents, the discovery of a side-effect, or a significant court ruling. The method proceeds from the recognition that factorial analysis of the event (development) can help predict how the news will be reported, which in turn can be used to predict the impact on stock price, or products sales, and other significant aspect of business performance.
Crisis-type stock price dynamics have been the subject of detailed analysis and modeling in the past, both academic and commercial. This is hardly surprising; billions of dollars are lost or, in some cases, earned, in the highly volatile stock-trading that often follows the breaking news of such sudden events. The input parameters of existing predictive impact models are typically the financial attributes of the event itself and the companies involved.
The disclosed method augments this approach with a new and fundamentally different class of attributes; communication parameters which can be used to predict the media coverage of the event.
The approach can be illustrated with an example. Company X announces the termination of a sponsorship contract with a high profile celebrity whose promotions of the company's products has been seen as effective. A few days later the company disappoints their investors by announcing a quarterly loss, rather than the expected profit. The news wires reportage mention the loss of the sponsorship in their reportage on the missed earnings target. Some of the reports are accompanied with a photo of the celebrity. Traditional market analysis will re-compute a new and lower price objective for the stock, based on lower earnings expectations. Some potential or actual stock owners will learn of the news through such financial analysis, but most will be exposed to the news through media, social or traditional. Such media reportage is not only a conduit for carrying factual and quantified information. The contextualization of the news, the sentiment of the reporting, the degree of disbursement, the linkage to pubic concerns and many other factors all contribute to the change in confidence in the stock and the demand for their products. These media coverage factors can, to some extent, be predicted, based on communication parameters around the news, such as the photo of the celebrity, and what other material is competing for media space at the same time.
The ability to predict media coverage is valuable in three different interdependent layers, each valuable in itself.                In its most elementary form it can guide the PR response        Secondly, and building on no 1, it can be used to predict the impact on product revenues        Thirdly, and building on no 2, on the confidence in a stock        
The disclosed method proceeds from the recognition that the business attributes of the event itself, and of the subject company, are often poor predictors for the volume and tonality of the media coverage, through which medium the markets will be informed and kept up-to date of the event/crisis/change. It is not that these parameters are invalid, but they are insufficient. As the disclosure will demonstrate, a sudden event or crisis and the corporation impacted by it, are associated with communication parameters as well as the business parameters already used by existing prediction models. These communication parameters include factors such as the quality of photographs, the level of convergence with current public concerns or fashions and the level of positive or negative endorsement by key influencers. The disclosed method permits the identification of such communication parameters for different types of events and it provides quantification of both the influence on the news coverage and on the resultant stock price movements product revenues.
The central principle of the methodology is that the communication factor can be derived by a three-step process: a) identify all the parameters with high correlations against stock price movements or product sales b) identify all the parameters which have a high correlation against the media impact c) all the parameters which have a high correlation against both the media, revenues and stock price are the ones with the highest predictive potential.
A related application (U.S. Provisional Patent Application No. 60/595,175 filed on Jun. 13, 2005) has been filed for examining the non-sudden but more sustained spread between analyst targets and stock prices by analyzing how investor confidence is influenced continuously by media coverage.